Fish farming plays a crucial role in aquaculture, where feed management is a key factor affecting productivity and operational costs. This research presents the design and implementation of an Internet of Things (IoT)-based automatic fish feeder system, integrated with a custom Android application. The system uses an ESP32 microcontroller to control a load cell sensor for accurate feed weighing, an ultrasonic sensor to monitor feed availability, servo motors for feed release mechanisms, and a DC motor for feed dispersion. Firebase Realtime Database serves as the data communication medium between the hardware and mobile application, enabling real-time control and monitoring. A rule-based control logic is implemented to execute scheduled or manual feeding processes. Experimental results show a feed weight accuracy of ±5 grams, with feeding operations completed within 1.5 minutes and an average throw distance of 287.8 cm. The system supports automatic alerts, scheduling, feed history logging, and remote access via the application. Compared to conventional manual methods, the system reduces feed waste, increases portion accuracy, and decreases feeding time by over 75%. These features demonstrate the system’s capability to enhance feeding efficiency, reduce labor dependency, and support sustainable and scalable fish farming practices through automation and real-time monitoring.